activity
20222026
most citedCloud gap-filling with deep learning for improved grassland monitoring

15 citations · 36 across the 18 of their papers we have counts for

collaborators
Showing 2022Show all

9 papers · 1 filter

cs.LG2022★ 5 cited

Evaluating Digital Agriculture Recommendations with Causal Inference

Ilias Tsoumas, Georgios Giannarakis, Vasileios Sitokonstantinou +5

In contrast to the rapid digitalization of several industries, agriculture suffers from low adoption of smart farming tools. While AI-driven digital agriculture tools can offer hig…

cs.LG2022★ 1 cited

Fuzzy clustering for the within-season estimation of cotton phenology

Vasileios Sitokonstantinou, Alkiviadis Koukos, Ilias Tsoumas +3

Crop phenology is crucial information for crop yield estimation and agricultural management. Traditionally, phenology has been observed from the ground; however Earth observation,…

cs.CV2022★ 3 cited

Towards Global Crop Maps with Transfer Learning

Hyun-Woo Jo, Alkiviadis Koukos, Vasileios Sitokonstantinou +2

The continuous increase in global population and the impact of climate change on crop production are expected to affect the food sector significantly. In this context, there is nee…

cs.LG2022★ 2 cited

Evaluating Digital Tools for Sustainable Agriculture using Causal Inference

Ilias Tsoumas, Georgios Giannarakis, Vasileios Sitokonstantinou +5

In contrast to the rapid digitalization of several industries, agriculture suffers from low adoption of climate-smart farming tools. Even though AI-driven digital agriculture can o…

cs.LG2022★ 3 cited

Personalizing Sustainable Agriculture with Causal Machine Learning

Georgios Giannarakis, Vasileios Sitokonstantinou, Roxanne Suzette Lorilla +1

To fight climate change and accommodate the increasing population, global crop production has to be strengthened. To achieve the "sustainable intensification" of agriculture, trans…

cs.CV2022★ 1 cited

A Data Cube of Big Satellite Image Time-Series for Agriculture Monitoring

Thanassis Drivas, Vasileios Sitokonstantinou, Iason Tsardanidis +3

The modernization of the Common Agricultural Policy (CAP) requires the large scale and frequent monitoring of agricultural land. Towards this direction, the free and open satellite…

cs.LG2022★ 1 cited

Pest presence prediction using interpretable machine learning

Ornela Nanushi, Vasileios Sitokonstantinou, Ilias Tsoumas +1

Helicoverpa Armigera, or cotton bollworm, is a serious insect pest of cotton crops that threatens the yield and the quality of lint. The timely knowledge of the presence of the ins…

cs.CV2022

Towards Space-to-Ground Data Availability for Agriculture Monitoring

George Choumos, Alkiviadis Koukos, Vasileios Sitokonstantinou +1

The recent advances in machine learning and the availability of free and open big Earth data (e.g., Sentinel missions), which cover large areas with high spatial and temporal resol…

cs.LG2022★ 3 cited

Towards assessing agricultural land suitability with causal machine learning

Georgios Giannarakis, Vasileios Sitokonstantinou, Roxanne Suzette Lorilla +1

Understanding the suitability of agricultural land for applying specific management practices is of great importance for sustainable and resilient agriculture against climate chang…